Nonlinear Efficiency of Bored Pile Group under Lateral Loading

A 3×3 bored pile group consisting of nine cast-in-drilled-hole reinforced concrete shafts and a comparable single-shaft were subjected to reversed cyclic, lateral head loading to investigate group interaction effects across a wide range of lateral displacements. The piles had the same diameter of d = 0.61?m and similar soil conditions; however, various equipment constraints led to two differences: (1) a fixed head (zero rotation) boundary condition for the single pile versus minor pile cap rotation in the vertical plane for the group and (2) shaft longitudinal reinforcement ratios of 1.8% for the single pile and 1% for the group piles. To enable comparisons between the test results, a calibrated model of the single pile (1.8% reinforcement) was developed and used to simulate the response of a single shaft with 1% reinforcement. Additional simulations of the pile group were performed to evaluate the effects of cap rotation on group response. By comparing the simulated responses for common conditions, i.e., 1% reinforcing ratio and zero head rotation, group efficiencies were found to range from unity at lateral displacements <0.004×d to 0.8 at small displacements ～ 0.01–0.02×d and up to 0.9 at failure (displacements >0.04×d). Hence, we find that group efficiency depends on the level of nonlinearity in the foundation system. The general group efficiency, although not its displacement-dependence, is captured by p-multipliers in the literature for reinforced concrete, fixed-head piles.     

Use of fuzzy logic for modeling, estimation, and prediction inswitched reluctance motor drives

Switched reluctance motor drives may be used in many commercial applications due to their simplicity and low cost. These drives require rotor position feedback to operate. However, in many systems, rotor position sensors have disadvantages. In this paper, a position sensorless scheme is described which uses fuzzy modeling, estimation and prediction. An important feature is that saturation and real-time nonideal effects are not ignored, but that no mathematical model is required. Instead, a fuzzy logic-based model is constructed from both static and real-time motor data, and from this model the rotor position is estimated. The system also incorporates fuzzy logic-based methods to provide a high robustness against noise. This includes a fuzzy predictive filter which combines both fuzzy logic-based time-series prediction, as well as a heuristic knowledge-based algorithm to detect and discard feedback signal error. In addition, the method uses heuristic knowledge to choose the most desirable phase for angle estimation in order to minimize the effect of feedback error. It is also shown that, by using fuzzy logic, the estimation scheme offers a high robustness and reliability and is thus well suited to a wide range of systems     

Seismic earth pressures on flexible cantilever retaining walls with deformable inclusions

In this study, the results of 1-g shaking table tests performed on small-scale flexible cantilever wallmodels retaining composite backfill made of a deformable geofoam inclusion and granular cohesionlessmaterial were presented. Two different polystyrene materials were utilized as deformable inclusions.Lateral dynamic earth pressures and wall displacements at different elevations of the retaining wallmodel were monitored during the tests. The earth pressures and displacements of the retaining wallswith deformable inclusions were compared with those of the models without geofoam inclusions.Comparisons indicated that geofoam panels of low stiffness installed against the retaining wall modelaffect displacement and dynamic lateral pressure profile along the wall height. Depending on the inclusioncharacteristics and the wall flexibility, up to 50% reduction in dynamic earth pressures wasobserved. The efficiency of load and displacement reduction decreased as the flexibility ratio of the wallmodel increased. On the other hand, dynamic load reduction efficiency of the deformable inclusionincreased as the amplitude and frequency ratio of the seismic excitation increased. Relative flexibility ofthe deformable layer （the thickness and the elastic stiffness of the polystyrene material） played animportant role in the amount of load reduction. Dynamic earth pressure coefficients were compared withthose calculated with an analytical approach. Pressure coefficients calculated with this method werefound to be in good agreement with the results of the tests performed on the wall model having lowflexibility ratio. It was observed that deformable inclusions reduce residual wall stresses observed at theend of seismic excitation thus contributing to the post-earthquake stability of the retaining wall. Thegraphs presented within this paper regarding the dynamic earth pressure coefficients versus the wallflexibility and inclusion characteristics may serve for the seismic design of full-scale retaining walls withdeformable polystyren     

Simple Nonlinear Model for Elastic Response of Cohesionless Granular Materials

A constitutive model based on hyperelasticity is proposed to capture the resilient (elastic) behavior of granular materials. Resilient behavior is a widely accepted idealization of the response of unbound granular layers of pavements, following shakedown. The coupling property of the proposed model accounts for shear dilatancy and pressure-dependent behavior of the granular materials. The model is calibrated using triaxial resilient test data obtained from the literature. A statistical comparison is made between the predictions of the proposed model and a few of the prominent models of resilient response. The proposed coupled hyperelastic model yields a significantly better fit to the experimental data. It also offers a computational efficiency when implemented in a classical nonlinear finite elemental framework.     

Predictive human operator model to be utilized as a controller using linear,neuro-fuzzy and fuzzy-ARX modeling techniques

Modeling human operator's behavior as a controller in a closed-loop control system recently finds applications in areas such as training of inexperienced operators by expert operator's model or developing warning systems for drivers by observing the driver model parameter variations. In this research, first, an experimental setup has been developed for collecting data from human operators as they controlled a nonlinear system. Appropriate reference signals and scenarios were designed according to the system identification and human operator modeling theory, to collect data from subjects. Different modeling schemes, namely ARX models as linear approach, and adaptive-network-based fuzzy inference system (ANFIS) as intelligent modeling approach have been evaluated. A hybrid modeling method, fuzzy-ARX (F-ARX) model, has been developed and its performance was found to be better in terms of predicting human operator's control actions as well as replacing the operator as a stand-alone controller. It has been concluded that F-ARX models can be a good alternative for modeling the human operator.     

Evaluation of trace metal contents of some wild edible mushrooms from Black sea region, Turkey

Fructification organs of Calvatia excipuliformis, Lycoperdon perlatum, Laccaria amethystea, Armillaria mellea, Marasmius oreades, Xerula radicata, Cantharellus cibarius, Craterellus cornucopioides, Cantharellus tubaeformis, Hypholoma fasciculare, Clitocybe gibba, Collybia dryophila, Lepista nuda and Mycena aetites were collected from different localities in Black sea region of Turkey. Their trace metals concentrations were determined by atomic absorption spectrometry after wet and microwave digestion. The results were (as mg/kg) 150–1741 for iron, 15.5–73.8 for copper, 28.6–145 for manganese, 43.5–205 for zinc, 4.8–42.7 for aluminium and 0.9–2.6 for lead. The levels of lead analyzed in some edible mushroom samples were found to be higher than legal limits. The relative standard deviations (R.S.D.) were found below 10%. The accuracy of procedure was confirmed by certified reference material.     

Prediction of manually controlled vessels’ position and course navigating in narrow waterways using Artificial Neural Networks

Despite modern navigation devices, there are still some problems for navigating of vessels in narrow waterways because of geographical structures and various disturbances. In this study, a guidance and an early warning method by means of predicting three-minute-ahead position of a vessel, especially in the turning points, has been developed for navigating in narrow waterways. The Istanbul Strait has been specifically studied as a model. Since operators in Vessel Traffic Services (VTS) can watch only straight bearing of vessels on VTS panels but especially for turning regions, they have to foresee a risk on time which may result in a disaster. The objective of this study is to predict the future coordinates of a manually controlled vessel using Artificial Neural Networks (ANN).Artificial Neural Networks have been trained by using position and speed data collected from vessels which navigated manually in the Strait. Three-minute-ahead position of vessels has been predicted by using the trained ANN. Some on-line experiments have been done in Istanbul VTS centre and it has been observed that the method satisfied the goal in especially turning points of the Strait. Hence the proposed method could be utilized for warning system by VTS operators and guidance system by vessel crew.     

In situ mullite foam fabrication using microwave energy

In situ mullite ceramic foams were fabricated using polymeric sponge replication method from ceramic slurry containing alpha alumina and kaolin mixtures. Ceramic preforms were processed using microwave energy and conventional heating. The sintered foam samples were characterized by SEM and XRD observations, density measurements and compression tests in order to observe the effect of two different sintering techniques on the structure and properties. It was found that the microwave processing was completed in a shorter burning out and sintering cycle and produced structures having higher mullite transformation ratio and fine grains.